Update app.py

app.py

@@ -11,7 +11,7 @@ def Model():
   return model, tokenizer
 
 def Predict(model, tokenizer, text):
-  res = tokenizer(s, padding=True, truncation=True, return_tensors="pt", max_length=512)
+  res = tokenizer(text, padding=True, truncation=True, return_tensors="pt", max_length=512)
   res = model(**res)
   logits = res.logits.softmax(dim=1)
   logits = logits.numpy()[0]#.cpu().detach().numpy()[0]
@@ -20,10 +20,10 @@ def Predict(model, tokenizer, text):
 def Print(logits, dictionary):
   z = zip(logits, np.arange(0, 8))
   z = sorted(z, key=lambda x: x[0], reverse=True)
-  sum, idx = 0, 0
-  while sum < 0.95:
+  summ, idx = 0, 0
+  while summ < 0.95:
     st.markdown(f"{idx + 1}. ", dictionary[z[idx][1]])
-    sum += z[idx][0]
+    summ += z[idx][0]
     idx += 1
 
 def filter(title, abstract):